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FINAL EXAM TOPIC LIST Chapter 1 Population vs Sample Chapter 2 Measures of Central Tendency: – Mean, Median and Mode - be able to compute these, what do they measure (properties) Measures of Variability: – Standard Deviation (Variance) - be able to compute, what does it measure Measures of Relative Standing: – Percentile and z-Score - what do they measure, how are they interpreted Chapter 3 Terms to understand: Sample Point, Sample Space, Event, Union, Intersection, and Complement Complement Law, Additive Law and Multipicative Law - know what they say, be able to apply them Conditional Probability, Independence, Mutually Exclusive and Combinations - know what they mean and how to apply them Chapter 4 Binomial Random Variable: – What are its Characteristics – Know how to use its Probability Distribution – Understand the use of its Mean and Standard Deviation (Variance) Chapter 5 What is the role of the standard normal distribution - how do we use the tables of a standard normal to evaluate its probabilities How is the standard normal distribution used to evaluate probabilities for a quantity that has any normal ditribution - be able to evaluate probabilities and work word problems for normal random variables Chapter 6 What is a sampling distribution - how is it useful - what does the Central Limit Theorem say - be able to apply it in a word problem Chapter 7 What is the proper interpretation of a confidence interval What is the point estimate of the population mean How do we construct a confidence interval for a population mean when the sample size is large How do we construct a confidence interval for a population mean when the sample size is not large - (what assumption is made about the population when the sample size is small) What is the point estimate for a population proportion How do we construct a confidence interval for the population proportion when the sample size is large Chapter 8 Tests of Hypotheses - null hypothesis, alternative hypothesis, type I error, type II error, test statistic, rejection region, significance level, use and interpretation of a p-value, proper wording of conclusions in a test of hypothesis Formulate and conduct a test of hypothesis about a population mean when n is large and when n is not large (what assumption is made in the latter case) Formulate and conduct a test of hypothesis about a population proportion when n is large Be able to compute and interpret a p-value for a large n problem setting Chapter 9 When the two samples are independent, find a confidence interval for or conduct a test of hypothesis about the difference between two population means ( ) when both sample sizes and are large. When the two samples are independent, find a confidence interval for or conduct a test of hypothesis about the difference between two population means ( ) when one or both sample sizes and are not large (what assumptions are made about the two populations in this case) When the two samples are independent, find a confidence interval for or conduct a test of hypothesis about the difference between two population proportions ( ) when both sample sizes and are large Find a confidence interval for or conduct a test of hypothesis about the difference between two population means ( ) when the observations come from a paired data setting - when should we use a paired data analysis, ie what is the purpose of pairing Chapter 11 What are the roles of the dependent and independent variables - interpret the slope and intercept What is the criterion for fitting the line - be able to find the best line and use it for prediction What is the model and how is estimated? How do we determine whether x is a useful linear predictor of y? - Be able to conduct this test What is the difference between estimating the average response at a particular x-value and predicting a response at that x-value? - What is the source of extra variability in the prediction interval? Be able to construct these intervals What does correlation represent - how is it measured - what is its unit of measurement - how is interpreted